ACE Exploring Atmosphere and Climate of the Earth Using GPS, GALILEO, and LEO-LEO Occultations Per H - PowerPoint PPT Presentation

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ACE Exploring Atmosphere and Climate of the Earth Using GPS, GALILEO, and LEO-LEO Occultations Per H

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GPS, GALILEO, and LEO-LEO Occultations. Per H eg (AIR/DMI) Gottfried Kirchengast (IGAM/UG) ... Radiosonde Humidity Profile (Kauai, Hawaii, 1 Oct 2000, 12UTC) ... – PowerPoint PPT presentation

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Title: ACE Exploring Atmosphere and Climate of the Earth Using GPS, GALILEO, and LEO-LEO Occultations Per H


1
ACEExploring Atmosphere and Climateof the
EarthUsingGPS, GALILEO, and LEO-LEO
OccultationsPer Høeg (AIR/DMI)Gottfried
Kirchengast (IGAM/UG)
2
Objectives
  • Climate
  • Monitoring global long-term variations in the
    climate and the forcings of the atmosphere system
    giving rise to trends
  • Atmosphere
  • Observe and analyze globally the physical
    condition and state of the atmosphere of the
    Earth to improve predictions of future state
  • Space Weather
  • Monitoring and modeling of ionosphere and
    plasmasphere electron density structures

3
Primary Issue of Concern Climate Change
  • Increasing evidence exists that the Earths
    climate is currently changing (e.g., IPCC 2001
    Report). The changes are most pronounced in the
    most variable component of the Earth system, the
    atmosphere.
  • Key indicators
  • Humidity and temperature in the troposphere
    tend to increase
  • Stratospheric temperatures tend to decrease
  • Stratospheric humidity tend to increase with
    drastic changes in the radiation
  • It is likely that these changes are associated
    with human-induced
  • increases of greenhouse gas concentrations
    in the atmosphere.
  • Natural variability of the climate system
    complicates the picture,
  • rendering proper understanding of climate
    change very challenging.

4
Variability of Atmospheric Water Vapor
Radiosonde Humidity Profile (Kauai, Hawaii, 1 Oct
2000, 12UTC)
Latitude-Height Slice of Humidity based on ECMWF
analysis (15 Sep 1999, 12UTC, 79W)
5
Water Vapor Variability
Column Water Vapor Monthly Map January 1994
Column Water Vapor Monthly Map July 1994
6
Greenhouse Gas Emissionsand Temperature Change
Projections
b) Corresponding near surface temperature
change projections
a) CO2 emission paths for several representative
IPCC scenarios
7
Present Observations
Global tropospheric and surface temperature data
from different sources (MSU MSU satellite data,
UKMO radiosonde-based data, Surface surface
data) Inset difference between surface and
radiosonde data
8
Scientific Objectives
  • Major goal
  • Monitor and describe variations and changes in
    the global atmospheric temperature and water
    vapor distribution
  • Assess climate changes caused by mass field
    changes and atmosphere dynamics.
  • Main objectives
  • To establish highly accurate (lt 0.025 g/kg and lt
    3 in specific humidity) and vertically resolved
    (lt 1 km) global climatology of water vapor in the
    troposphere
  • To establish a highly accurate (lt 0.2 K) and
    vertically resolved (1 km) global climatology of
    temperature in the troposphere and the
    stratosphere
  • To perform research on climate variability and
    climate change together with research in improved
    atmospheric models as well as advancements in
    NWP
  • To study troposphere structures in polar and
    equatorial regions
  • To support analysis and validation of data from
    other space missions
  • To demonstrate a new and novel active atmospheric
    sounding technique with the CALL instrument
  • To enhance the European observational capability
    for improved contribution to the international
    GCOS initiative.
  • Advances in atmosphere physics and climate change
    processes
  • Global climate warming and increased averaged
    atmospheric water vapor levels
  • Tropical heat and mass exchange with
    extra-tropical regions
  • Transport across subtropical mixing barriers,
    relevant for information on the lifetime of
    greenhouse gases
  • Stratospheric winds and temperatures and
    atmospheric wave phenomena
  • Polar front dynamics and mass exchange together
    with tropospheric water vapor feedback on climate
    stability

9
Satellite Constellation
  • 4 micro-satellites
  • Mass 130 kg
  • Power 80 W
  • Stable two-plane constellation in 90 degrees
    inclination
  • In each plane, counter-rotating orbits with 2
    satellites - for optimizing quality of
    measurements
  • Two altitudes
  • Heights 650 km and 850 km to optimize spatial
    distribution of occultations
  • Orbital local time drift
  • To optimize the temporal and local time
    distribution of occultations
  • Instruments
  • L-band GPS/GALILEO precision receiver
  • X/K-band LEO-LEO precision transmitter and
    receiver (2 of each)

10
(No Transcript)
11
Why is measurements ofatmospheric water vapor
important ?
  • Indicator of climate change
  • Strongest greenhouse gas
  • Climate positive/negative feedback
  • Energy reservoir
  • Impact/feedback on global wind system changes and
    general atmosphere dynamics
  • Hydrologic cycle
  • Highly variable (time and space)

12
Global Temperature Deviations
13
Forcing residuals in atmospheric models
  • Estimation of the residual (R) requires
    availability of high quality observed data.
  • Forcing residuals can be used to
  • identify tendency errors in the differential
    equations of atmospheric models
  • detect temporal variations in external forcing of
    the atmosphere.

14
Weak nudging towards the re-analyses

Data assimilation via nudging
Discretization in time (assimilation in spectral
space)
Forcing residual is approximated by the last
fraction
15
The ACE Experiment
16
GRAS Temperature Retrieval
17
Processing Steps for Water Vapor Retrievals
18
GRAS Requirements
19
Absorption at X/K-band frequencies
Frequencies 10.0-11.5 GHz 17.2-17.3
GHz 22.5-23.5 GHz
20
Absorption
21
CALL Temperature and Humidity Retrieval
22
CALLTemperatureand HumidityRequirements
23
Weekly Profile Coverage
Weekly latitudinal distribution of occultations.
Longitudinal variations still exist in the seven
days simulation. Part of the spread in the plot
is due to this effect. For the 500 x 500 km
cells the following statistics can be
calculated Average number of occultations in a
cell 22.49 Standard deviation 10.36
Average time difference (min) between profiles in
each cell as function of latitude. The simulation
covers a whole week of data. Average time
difference between the occultations 482 min
8h 2min Standard deviation 216 min 3h
36min
24
Global Distribution of Occultations
25
Distribution of NWP Radiosonde Observations
26
Global Distribution of LEO-LEO Occultations
27
Global Humidity Fields
28
  • Launch
  • 2006/2007
  • Mission lifetime
  • 5 years (2006 2012)
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